5 Steps to Wrangle Uncontrolled Data Flow

Step 3: Stop Muddling with Middleware

The decades-old middleware approach to integration (i.e., ESBs, EAIs, ETL) came of age when ERPs were the heavyweights of enterprise software. The middleware model was well matched to the integration needs of its time, but, today, its large installation footprint, heavy reliance on network processing, and use of older languages and protocols make it a less than ideal integration tool at a time when agility above all else is required to accommodate ever-changing cloud endpoints.

Given the long implementation cycles and high infrastructure and personnel costs, IT organizations should no longer invest in keeping middleware implementations current. While it's probably unrealistic to rip and replace, steps should be taken to begin migrating integration functionality to more modern cloud-based models such as data platform as a service (dPaaS).

Data is everywhere. Close inspection of a runner's shoes, a dog's collar, a prescription bottle, or even a keg of beer could reveal a flow of hidden data. And if your local pub isn't analyzing beer consumption through connected kegs today, it likely will be tomorrow. Analysts predict that the Internet of Things (IoT) will grow to encompass as many as 200 billion connected devices by 2020.

Couple the exploding IoT with other exploding data sources such as specialized cloud applications, social media feeds and mobile devices, and it's clear that there is no shortage of data for businesses to mine. Unfortunately, just as businesses have more data than ever to monetize, the data itself is becoming increasingly uncooperative as it ramps up in volume, variety and velocity — with no end in sight.

So how do you turn opportunity into insight? In this slideshow, Rob Consoli, senior vice president of sales and marketing, North America at Liaison Technologies, has compiled five tips on how to wrangle uncontrolled data flow in your enterprise.

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